Realizing the Promise of Disaggregated Data and Analytics for Social Justice Through Community Engagement and Intersectoral Research Partnerships

A. Kaida, Jill Anderson, Christine Barnard, L. Bartram, Daniel Bert, Sheelagh Carpendale, Charmaine Dean, Donald Estep, J. Etowa, M. Gislason, Genesa Greening, Mehrdad Hariri, Dawn Hoogeveen, Dalya Israel, A. Johal, A. Kennedy, K. McKenzie, R. Mendenhall, Nahed Mourad, V. Nicholson, Kelly Nolan, Zoë Osborne, Fred Popowich, Alexa Reedman, John Simpson, Julia Smith, M. Smith
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Abstract

In Canada, community and policy leaders have issued urgent calls to collect, analyze, and mobilize disaggregated data to inform equity-oriented initiatives aimed at addressing systemic racism and gender inequity, as well as other social inequities. This essay presents critical reflections from a national Roundtable discussion regarding how meaningful community engagement within academia–community–government research collaborations offers the opportunity to harness disaggregated data and advanced analytics to centre and address the priorities of equity-deserving and sovereignty-seeking groups. Participants emphasized four key priorities: (1) Building equitable and engaged partnerships that centre community-driven priorities and address structural barriers to community engagement; (2) Co-creating ethical data governance policies and infrastructure to support community data ownership and access; (3) Stimulating innovation and pursuing community involvement to create contextualized, advanced analyses and effective visualizations of disaggregated data; and (4) Building the capacity of all partners to effectively contribute to partnership goals. Capacity building was viewed as a bridge across a diversity of lived and professional expertise, enabling intersectoral research teams to collaborate in culturally safe and respectful ways. Beyond identifying key structural barriers impeding the promise of disaggregated data, we present practical opportunities for innovation in community-engaged scholarship to address social justice challenges in Canada. 
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通过社区参与和部门间研究伙伴关系实现分类数据和分析促进社会正义的承诺
在加拿大,社区和政策领导人已发出紧急呼吁,要求收集、分析和动员分类数据,为旨在解决系统性种族主义和性别不平等以及其他社会不平等问题的以公平为导向的倡议提供信息。本文提出了一次全国性圆桌会议讨论的重要反思,讨论了学术界-社区-政府研究合作中有意义的社区参与如何提供机会,利用分类数据和高级分析来集中和解决公平应得和主权寻求群体的优先事项。与会者强调了四个关键优先事项:(1)建立公平和参与的伙伴关系,以社区驱动的优先事项为中心,解决社区参与的结构性障碍;(2)共同创建道德数据治理政策和基础设施,以支持社区数据所有权和访问;(3)鼓励创新和追求社区参与,以创建情境化的、先进的分析和有效的分类数据可视化;(4)建立所有合作伙伴有效促进伙伴关系目标的能力。能力建设被视为跨越生活和专业知识多样性的桥梁,使跨部门研究团队能够以文化安全和尊重的方式进行合作。除了确定阻碍分类数据前景的关键结构性障碍之外,我们还提出了社区参与奖学金创新的实际机会,以解决加拿大的社会正义挑战。
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